CTS-IGERT is pleased to host a seminar by Piotr Szczurek, entitled "Machine Learning Approach to Report Prioritization with an Application to Travel Time Dissemination", on Tuesday, September 22nd at 11:00 a.m. in Room 1000 SEO.

Abstract:
Our work looks at the problem of data prioritization, commonly found in mobile ad-hoc networks. The proposed general solution uses a machine learning approach in order to learn the relevance value of reports, which represent sensed data. The general solution is then applied to a travel time dissemination application. Through the use of offline learning, the paper analyzes the feasibility of the proposed approach and compares the accuracy performance of several common machine learning algorithms. The results show that not all machine learning algorithms may be used for prioritization and that the use of the logistic regression algorithm is particularly suited for the problem. The learned logistic regression model is then used in a simulated VANET environment. The results of the simulations show that it is better at prioritizing reports in terms of their usefulness in aiding vehicles to choose the shortest travel time paths.:

Biography:
Piotr Szczurek is a 4th year Ph.D. in the Computer Science department at UIC. He has been involved in the Computational Transportation Science IGERT program since its beginning in 2006. His undergraduate degree was completed in 2005at University of Illinois at Chicago. Currently, he is working with Professor Ouri Wolfson from Computer Science department as his primary advisor and Professor Jie Lin from the department of Civil and Materials Engineering as his secondary advisor. His research focuses on applications of data dissemination in vehicular ad-hoc networks for use in travel information systems.: